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Sebina Shrestha

Researcher at Texas A&M University

Publications -  23
Citations -  449

Sebina Shrestha is an academic researcher from Texas A&M University. The author has contributed to research in topics: Fluorescence-lifetime imaging microscopy & Optical coherence tomography. The author has an hindex of 12, co-authored 23 publications receiving 416 citations. Previous affiliations of Sebina Shrestha include CERN & Kansas State University.

Papers
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Journal ArticleDOI

A dual-modality optical coherence tomography and fluorescence lifetime imaging microscopy system for simultaneous morphological and biochemical tissue characterization

Jesung Park, +5 more
- 02 Aug 2010 - 
TL;DR: A dual-modality system, incorporating optical coherence tomography (OCT) and fluorescence lifetime imaging microscopy (FLIM), that is capable of simultaneously characterizing the 3-D tissue morphology and its biochemical composition is developed.
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High-speed multispectral fluorescence lifetime imaging implementation for in vivo applications

Sebina Shrestha, +5 more
- 01 Aug 2010 - 
TL;DR: This work presents a cost-effective scanning multispectral FLIM implementation capable of achieving pixel rates on the order of tens of kilohertz, which will facilitate the evaluation of FLIM for in vivo applications.
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Measurement of top quark–antiquark pair production in association with a W or Z boson in pp collisions at √s = 8 TeV

Khachatryan, +2130 more
- 17 Sep 2014 - 
TL;DR: In this article, a measurement of the cross section for the production of top quark-antiquark pairs (ttbar) in association with a vector boson V (W or Z) in proton-proton collisions at square root(s) = 8 TeV is presented.
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Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy.

Jesung Park, +5 more
- 01 Feb 2012 - 
TL;DR: The endogenous multispectral FLIM approach, which can readily be adapted for in vivo intravascular catheter based imaging, is capable of reliably identifying plaques with high content of either collagen or lipids.
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Automated classification of optical coherence tomography images for the diagnosis of oral malignancy in the hamster cheek pouch

Paritosh Pande, +8 more
- 01 Aug 2014 - 
TL;DR: The results of the study demonstrate the feasibility of using quantitative image analysis algorithms for extracting morphological features from OCT images to perform the automated diagnosis of oral malignancies in a hamster cheek pouch model.